Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration on each subsystem to futher reduce the hardware requirements. The DNN was designed using a system generator and implemented using very hardware description language (VHDL). The system achievments outcomes the superior’s accuracy rate of approximately 99.6 percent in distinguishing bengin from malignant tissue. Also, the hardware resources were reduced by 30 percent from works of literature with an error rate of 7e-4 when using the Kintex-7 xc7k325t-3fbg676 board.
In recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. T
... Show MoreIn the present work, a density functional theory (DFT) calculation to simulate reduced graphene oxide (rGO) hybrid with zinc oxide (ZnO) nanoparticle's sensitivity to NO2 gas is performed. In comparison with the experiment, DFT calculations give acceptable results to available bond lengths, lattice parameters, X-ray photoelectron spectroscopy (XPS), energy gaps, Gibbs free energy, enthalpy, entropy, etc. to ZnO, rGO, and ZnO/rGO hybrid. ZnO and rGO show n-type and p-type semiconductor behavior, respectively. The formed p-n heterojunction between rGO and ZnO is of the staggering gap type. Results show that rGO increases the sensitivity of ZnO to NO2 gas as they form a hybrid. ZnO/rGO hybrid has a higher number of vacancies that can b
... Show MoreObjective: To identify the role and importance of the clinical pharmacist in the Emergency Department on prevent
or reduced the medication error.
Methodology: We collected the medical file of 3400 patients, 1400 patient's file in (A) hospital, and 1000 patient's
file in each of (B and C) hospital, who admitted to the ED, at primary weekdays between 8 am to 2 pm, and
recorded all the intervention made by clinical pharmacist through an active search in clinical charts, with analysis
of the daily medical prescription. The potential severity of harm of the medication error judged by two reviewers,
a permanent emergency physician, and clinical pharmacist based on the National Coordinating Council (NCC) of
Medication Error
This Paper assesses the knowledge management system (KMS) requirements at Al-Ameed University concerning ISO 30401:2022. Specifically, the research aims to ascertain the degree to which international standards have been complied with and gaps that have been identified. A case study was conducted using field observations, interviews, and checklists to assess the institution's compliance with the KMS framework. The level of implementation and documentation of knowledge management processes was assessed using a seven-point scale. The findings reveal that Al-Ameed University has severe gaps in knowledge creation, sharing, and support for knowledge management in terms of strategic leadership. While certain elements like availability of r
... Show MoreBackground: Radiologic evaluation of breast lesions is being achieved through several imaging modalities. Mammography has an established role in breast cancer screening and diagnosis. Still however, it shows some limitations particulary in dense breast.
Methods : Magnetic resonance imaging is an attractive tool for the diagnosis of breast tumors1 and the use of magnetic resonance imaging of the breast is rapidly increasing as this technique becomes more widely available.1 As an adjunct to mammography and ultrasound, MRI can be a valuable addition to the work-up of a breast abnormality. MRI has the advantages of providing a three-dimensional view of the breast, performing wit
... Show MoreDiscriminant between groups is one of the common procedures because of its ability to analyze many practical phenomena, and there are several methods can be used for this purpose, such as linear and quadratic discriminant functions. recently, neural networks is used as a tool to distinguish between groups.
In this paper the simulation is used to compare neural networks and classical method for classify observations to group that is belong to, in case of some variables that don’t follow the normal distribution. we use the proportion of number of misclassification observations to the all observations as a criterion of comparison.
The gamma camera, along with SPECT and PET scanners, is one of the main imaging technologies in nuclear medicine. A collimator is typically constructed from tungsten to provide high absorption of gamma photon energies. It has a hole or holes for imaging. Gamma rays from a radioactive source within the body are emitted in all directions, while the photons required constructing an image travel through the hole. A scintillator is the most common material used to convert the high energy of gamma radiation into a lowenergy optical photon. These detectors are one of the primary secrets to radio-diagnosis in nuclear medicine. The photomultiplier tube (PMT) is a versatile device with extraordinarily highly sensitivity and response. A typical photom
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